Feature Extraction
Transformers
PyTorch
English
apex
music
audio
popularity-prediction
aesthetic-quality
multi-task-learning
mert
ai-generated-music
suno
udio
custom_code
Instructions to use amaai-lab/apex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amaai-lab/apex with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="amaai-lab/apex", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("amaai-lab/apex", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload config.json with huggingface_hub
Browse files- config.json +1 -3
config.json
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"APEXModel"
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"epoch": 50,
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"val_loss": 398.77835954938615
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"trained_on": "Suno + Udio (~211k songs, ~10k hours)",
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"loss_type": "uncertainty_weighted"
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}
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"APEXModel"
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],
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"epoch": 50,
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"val_loss": 398.77835954938615
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}
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